def test_calc_data_fast_uint8():
data = da.random.randint(
0,
100,
size=(100_000, 1000, 1000),
chunks=(1, 1000, 1000),
dtype=np.uint8,
)
assert calc_data_range(data) == [0, 255]
def test_calc_data_range():
# all zeros should return [0, 1] by default
data = np.zeros((10, 10))
clim = calc_data_range(data)
assert np.all(clim == [0, 1])
# all ones should return [0, 1] by default
data = np.ones((10, 10))
clim = calc_data_range(data)
assert np.all(clim == [0, 1])
# return min and max
data = np.random.random((10, 15))
data[0, 0] = 0
data[0, 1] = 2
clim = calc_data_range(data)
assert np.all(clim == [0, 2])
# return min and max
data = np.random.random((6, 10, 15))
data[0, 0, 0] = 0
data[0, 0, 1] = 2
clim = calc_data_range(data)
assert np.all(clim == [0, 2])
# Try large data
data = np.zeros((1000, 2000))
data[0, 0] = 0
data[0, 1] = 2
clim = calc_data_range(data)
assert np.all(clim == [0, 2])
# Try large data mutlidimensional
data = np.zeros((3, 1000, 1000))
data[0, 0, 0] = 0
data[0, 0, 1] = 2
clim = calc_data_range(data)
assert np.all(clim == [0, 2])
def test_calc_data_range_fast_big():
val = calc_data_range(data_dask)
assert len(val) > 0
def test_calc_data_range_fast_big():
data = da.random.random(size=(100_000, 1000, 1000), chunks=(1, 1000, 1000))
t0 = time.time()
_ = calc_data_range(data)
t1 = time.time()
assert t1 - t0 < 2